This study aimed to determine an optimal model involving thoracic electrical impedance tomography (EIT) metrics and patient geometric information to best correlate to standard pulmonary function test (PFT) measures in a cohort of 32 ALS patients and 32 age-matched healthy controls. Thoracic EIT is a non-invasive technology in which an electrode belt chest allows for real-time impedance imaging of respiratory function. The optimal form of the model was determined via a genetic algorithm a novel technique for model generation in EIT applications. Combining multiple metrics yielded optimal r values of 0.62 and 0.66 for 1- and 2-term regression models optimized. The results appear very promising and further refinement of the technology appears warranted.
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| http://dx.doi.org/10.1109/EMBC53108.2024.10781742 | DOI Listing |
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